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360 Degree View Camera Based Visual ...

Rochester Institute of Technology.

360 Degree View Camera Based Visual Assistive Technology for Contextual Scene Information.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	360 Degree View Camera Based Visual Assistive Technology for Contextual Scene Information./
Author:	Ali, Mazin.
Description:	1 online resource (54 pages)
Notes:	Source: Masters Abstracts International, Volume: 56-06.
Subject:	Robotics. -
Online resource:	click for full text (PQDT)
ISBN:	9780355203783

360 Degree View Camera Based Visual Assistive Technology for Contextual Scene Information.
Ali, Mazin.

360 Degree View Camera Based Visual Assistive Technology for Contextual Scene Information. - 1 online resource (54 pages)

Source: Masters Abstracts International, Volume: 56-06.

Thesis (M.S.)--Rochester Institute of Technology, 2017.

Includes bibliographical references

In this research project, a system is proposed to aid the visually impaired by providing partial contextual information of the surroundings using 360° view camera combined with deep learning is proposed. The system uses a 360° view camera with a mobile device to capture surrounding scene information and provide contextual information to the user in the form of audio. The system could also be used for other applications such as logo detection which visually impaired users can use for shopping assistance.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355203783Subjects--Topical Terms:

561941
Robotics.
Index Terms--Genre/Form:

554714
Electronic books.

360 Degree View Camera Based Visual Assistive Technology for Contextual Scene Information.
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020 $a 9780355203783
035 $a (MiAaPQ)AAI10621991
035 $a (MiAaPQ)rit:12783
035 $a AAI10621991
040 $a MiAaPQ $b eng $c MiAaPQ
100 1 $a Ali, Mazin. $3 1184408
245 1 0 $a 360 Degree View Camera Based Visual Assistive Technology for Contextual Scene Information.
264 0 $c 2017
300 $a 1 online resource (54 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 56-06.
500 $a Adviser: Ferat Sahin.
502 $a Thesis (M.S.)--Rochester Institute of Technology, 2017.
504 $a Includes bibliographical references
520 $a In this research project, a system is proposed to aid the visually impaired by providing partial contextual information of the surroundings using 360° view camera combined with deep learning is proposed. The system uses a 360° view camera with a mobile device to capture surrounding scene information and provide contextual information to the user in the form of audio. The system could also be used for other applications such as logo detection which visually impaired users can use for shopping assistance.
520 $a The scene information from the spherical camera feed is classified by identifying objects that contain contextual information of the scene. That is achieved using convolutional neural networks (CNN) for classification by leveraging CNN transfer learning properties using the pre-trained VGG-19 network. There are two challenges related to this paper, a classification and a segmentation challenge. As an initial prototype, we have experimented with general classes such restaurants, coffee shops and street signs. We have achieved a 92.8% classification accuracy in this research project.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Robotics. $3 561941
650 4 $a Computer engineering. $3 569006
650 4 $a Electrical engineering. $3 596380
650 4 $a Artificial intelligence. $3 559380
650 4 $a Biomedical engineering. $3 588770
655 7 $a Electronic books. $2 local $3 554714
690 $a 0771
690 $a 0464
690 $a 0544
690 $a 0800
690 $a 0541
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Rochester Institute of Technology. $b Electrical Engineering. $3 1184409
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10621991 $z click for full text (PQDT)

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